facet_solver/

lib.rs

#![cfg_attr(not(feature = "std"), no_std)]
#![doc = include_str!("../README.md")]

extern crate alloc;

use alloc::borrow::Cow;
use alloc::collections::BTreeMap;
use alloc::collections::BTreeSet;
use alloc::string::{String, ToString};
use alloc::vec;
use alloc::vec::Vec;
use core::fmt;

use facet_core::{Def, Field, Shape, StructType, Type, UserType, Variant};

// Re-export resolution types from facet-reflect
pub use facet_reflect::{
    DuplicateFieldError, FieldInfo, FieldPath, KeyPath, MatchResult, PathSegment, Resolution,
    VariantSelection,
};

/// Cached schema for a type that may contain flattened fields.
///
/// This is computed once per Shape and can be cached forever since
/// type information is static.
#[derive(Debug)]
pub struct Schema {
    /// The shape this schema is for (kept for future caching key)
    #[allow(dead_code)]
    shape: &'static Shape,

    /// All possible resolutions of this type.
    /// For types with no enums in flatten paths, this has exactly 1 entry.
    /// For types with enums, this has one entry per valid combination of variants.
    resolutions: Vec<Resolution>,

    /// Inverted index: field_name → bitmask of configuration indices.
    /// Bit i is set if `resolutions[i]` contains this field.
    /// Uses a `Vec<u64>` to support arbitrary numbers of resolutions.
    field_to_resolutions: BTreeMap<&'static str, ResolutionSet>,
}

/// Handle that identifies a specific resolution inside a schema.
#[derive(Debug, Clone, Copy)]
pub struct ResolutionHandle<'a> {
    index: usize,
    resolution: &'a Resolution,
}

impl<'a> PartialEq for ResolutionHandle<'a> {
    fn eq(&self, other: &Self) -> bool {
        self.index == other.index
    }
}

impl<'a> Eq for ResolutionHandle<'a> {}

impl<'a> ResolutionHandle<'a> {
    /// Internal helper to build a handle for an index within a schema.
    fn from_schema(schema: &'a Schema, index: usize) -> Self {
        Self {
            index,
            resolution: &schema.resolutions[index],
        }
    }

    /// Resolution index within the originating schema.
    pub const fn index(self) -> usize {
        self.index
    }

    /// Access the underlying resolution metadata.
    pub const fn resolution(self) -> &'a Resolution {
        self.resolution
    }
}

/// A set of configuration indices, stored as a bitmask for O(1) intersection.
#[derive(Debug, Clone, PartialEq, Eq)]
pub struct ResolutionSet {
    /// Bitmask where bit i indicates `resolutions[i]` is in the set.
    /// For most types, a single u64 suffices (up to 64 configs).
    bits: Vec<u64>,
    /// Number of resolutions in the set.
    count: usize,
}

impl ResolutionSet {
    /// Create an empty config set.
    fn empty(num_resolutions: usize) -> Self {
        let num_words = num_resolutions.div_ceil(64);
        Self {
            bits: vec![0; num_words],
            count: 0,
        }
    }

    /// Create a full config set (all configs present).
    fn full(num_resolutions: usize) -> Self {
        let num_words = num_resolutions.div_ceil(64);
        let mut bits = vec![!0u64; num_words];
        // Clear bits beyond num_resolutions
        if !num_resolutions.is_multiple_of(64) {
            let last_word_bits = num_resolutions % 64;
            bits[num_words - 1] = (1u64 << last_word_bits) - 1;
        }
        Self {
            bits,
            count: num_resolutions,
        }
    }

    /// Insert a configuration index.
    fn insert(&mut self, idx: usize) {
        let word = idx / 64;
        let bit = idx % 64;
        if self.bits[word] & (1u64 << bit) == 0 {
            self.bits[word] |= 1u64 << bit;
            self.count += 1;
        }
    }

    /// Intersect with another config set in place.
    fn intersect_with(&mut self, other: &ResolutionSet) {
        self.count = 0;
        for (a, b) in self.bits.iter_mut().zip(other.bits.iter()) {
            *a &= *b;
            self.count += a.count_ones() as usize;
        }
    }

    /// Get the number of resolutions in the set.
    fn len(&self) -> usize {
        self.count
    }

    /// Check if empty.
    fn is_empty(&self) -> bool {
        self.count == 0
    }

    /// Get the first (lowest) configuration index in the set.
    fn first(&self) -> Option<usize> {
        for (word_idx, &word) in self.bits.iter().enumerate() {
            if word != 0 {
                return Some(word_idx * 64 + word.trailing_zeros() as usize);
            }
        }
        None
    }

    /// Iterate over configuration indices in the set.
    fn iter(&self) -> impl Iterator<Item = usize> + '_ {
        self.bits.iter().enumerate().flat_map(|(word_idx, &word)| {
            (0..64).filter_map(move |bit| {
                if word & (1u64 << bit) != 0 {
                    Some(word_idx * 64 + bit)
                } else {
                    None
                }
            })
        })
    }
}

/// Find fields that could disambiguate between resolutions.
/// Returns fields that exist in some but not all resolutions.
fn find_disambiguating_fields(configs: &[&Resolution]) -> Vec<String> {
    if configs.len() < 2 {
        return Vec::new();
    }

    // Collect all field names across all configs
    let mut all_fields: BTreeSet<&str> = BTreeSet::new();
    for config in configs {
        for name in config.fields().keys() {
            all_fields.insert(name);
        }
    }

    // Find fields that are in some but not all configs
    let mut disambiguating = Vec::new();
    for field in all_fields {
        let count = configs.iter().filter(|c| c.field(field).is_some()).count();
        if count > 0 && count < configs.len() {
            disambiguating.push(field.to_string());
        }
    }

    disambiguating
}

/// Information about a missing required field for error reporting.
#[derive(Debug, Clone)]
pub struct MissingFieldInfo {
    /// The serialized field name (as it appears in input)
    pub name: &'static str,
    /// Full path to the field (e.g., "backend.connection.port")
    pub path: String,
    /// The Rust type that defines this field
    pub defined_in: String,
}

impl MissingFieldInfo {
    /// Create from a FieldInfo
    fn from_field_info(info: &FieldInfo) -> Self {
        Self {
            name: info.serialized_name,
            path: info.path.to_string(),
            defined_in: info.value_shape.type_identifier.to_string(),
        }
    }
}

/// Information about why a specific candidate (resolution) failed to match.
#[derive(Debug, Clone)]
pub struct CandidateFailure {
    /// Human-readable description of the variant (e.g., "DatabaseBackend::Postgres")
    pub variant_name: String,
    /// Required fields that were not provided in the input
    pub missing_fields: Vec<MissingFieldInfo>,
    /// Fields in the input that don't exist in this candidate
    pub unknown_fields: Vec<String>,
    /// Number of unknown fields that have "did you mean?" suggestions for this candidate
    /// Higher = more likely the user intended this variant
    pub suggestion_matches: usize,
}

/// Suggestion for a field that might have been misspelled.
#[derive(Debug, Clone)]
pub struct FieldSuggestion {
    /// The unknown field from input
    pub unknown: String,
    /// The suggested correct field name
    pub suggestion: &'static str,
    /// Similarity score (0.0 to 1.0, higher is more similar)
    pub similarity: f64,
}

/// Errors that can occur when building a schema.
#[derive(Debug, Clone)]
pub enum SchemaError {
    /// A field name appears from multiple sources (parent struct and flattened struct)
    DuplicateField(DuplicateFieldError),
}

impl From<DuplicateFieldError> for SchemaError {
    fn from(err: DuplicateFieldError) -> Self {
        SchemaError::DuplicateField(err)
    }
}

impl fmt::Display for SchemaError {
    fn fmt(&self, f: &mut fmt::Formatter<'_>) -> fmt::Result {
        match self {
            SchemaError::DuplicateField(err) => {
                write!(
                    f,
                    "Duplicate field name '{}' from different sources: {} vs {}. \
                     This usually means a parent struct and a flattened struct both \
                     define a field with the same name.",
                    err.field_name, err.first_path, err.second_path
                )
            }
        }
    }
}

#[cfg(feature = "std")]
impl std::error::Error for SchemaError {}

/// Errors that can occur during flatten resolution.
#[derive(Debug, Clone)]
pub enum SolverError {
    /// No configuration matches the input fields
    NoMatch {
        /// The input fields that were provided
        input_fields: Vec<String>,
        /// Missing required fields (from the closest matching config) - simple names for backwards compat
        missing_required: Vec<&'static str>,
        /// Missing required fields with full path information
        missing_required_detailed: Vec<MissingFieldInfo>,
        /// Unknown fields that don't belong to any config
        unknown_fields: Vec<String>,
        /// Description of the closest matching configuration
        closest_resolution: Option<String>,
        /// Why each candidate failed to match (detailed per-candidate info)
        candidate_failures: Vec<CandidateFailure>,
        /// "Did you mean?" suggestions for unknown fields
        suggestions: Vec<FieldSuggestion>,
    },
    /// Multiple resolutions match the input fields
    Ambiguous {
        /// Descriptions of the matching resolutions
        candidates: Vec<String>,
        /// Fields that could disambiguate (unique to specific configs)
        disambiguating_fields: Vec<String>,
    },
}

impl fmt::Display for SolverError {
    fn fmt(&self, f: &mut fmt::Formatter<'_>) -> fmt::Result {
        match self {
            SolverError::NoMatch {
                input_fields,
                missing_required: _,
                missing_required_detailed,
                unknown_fields,
                closest_resolution,
                candidate_failures,
                suggestions,
            } => {
                write!(f, "No matching configuration for fields {input_fields:?}")?;

                // Show per-candidate failure reasons if available
                if !candidate_failures.is_empty() {
                    write!(f, "\n\nNo variant matched:")?;
                    for failure in candidate_failures {
                        write!(f, "\n  - {}", failure.variant_name)?;
                        if !failure.missing_fields.is_empty() {
                            let names: Vec<_> =
                                failure.missing_fields.iter().map(|m| m.name).collect();
                            if names.len() == 1 {
                                write!(f, ": missing field '{}'", names[0])?;
                            } else {
                                write!(f, ": missing fields {names:?}")?;
                            }
                        }
                        if !failure.unknown_fields.is_empty() {
                            if failure.missing_fields.is_empty() {
                                write!(f, ":")?;
                            } else {
                                write!(f, ",")?;
                            }
                            write!(f, " unknown fields {:?}", failure.unknown_fields)?;
                        }
                    }
                } else if let Some(config) = closest_resolution {
                    // Fallback to closest match if no per-candidate info
                    write!(f, " (closest match: {config})")?;
                    if !missing_required_detailed.is_empty() {
                        write!(f, "; missing required fields:")?;
                        for info in missing_required_detailed {
                            write!(f, " {} (at path: {})", info.name, info.path)?;
                        }
                    }
                }

                // Show unknown fields with suggestions
                if !unknown_fields.is_empty() {
                    write!(f, "\n\nUnknown fields: {unknown_fields:?}")?;
                }
                for suggestion in suggestions {
                    write!(
                        f,
                        "\n  Did you mean '{}' instead of '{}'?",
                        suggestion.suggestion, suggestion.unknown
                    )?;
                }

                Ok(())
            }
            SolverError::Ambiguous {
                candidates,
                disambiguating_fields,
            } => {
                write!(f, "Ambiguous: multiple resolutions match: {candidates:?}")?;
                if !disambiguating_fields.is_empty() {
                    write!(
                        f,
                        "; try adding one of these fields to disambiguate: {disambiguating_fields:?}"
                    )?;
                }
                Ok(())
            }
        }
    }
}

#[cfg(feature = "std")]
impl std::error::Error for SolverError {}

/// Compute a specificity score for a shape. Lower score = more specific.
///
/// This is used to disambiguate when a value could satisfy multiple types.
/// For example, the value `42` fits both `u8` and `u16`, but `u8` is more
/// specific (lower score), so it should be preferred.
/// Compute a specificity score for a shape.
///
/// Lower score = more specific type. Used for type-based disambiguation
/// where we want to try more specific types first (e.g., u8 before u16).
pub fn specificity_score(shape: &'static Shape) -> u64 {
    // Use type_identifier to determine specificity
    // Smaller integer types are more specific
    match shape.type_identifier {
        "u8" | "i8" => 8,
        "u16" | "i16" => 16,
        "u32" | "i32" | "f32" => 32,
        "u64" | "i64" | "f64" => 64,
        "u128" | "i128" => 128,
        "usize" | "isize" => 64, // Treat as 64-bit
        // Other types get a high score (less specific)
        _ => 1000,
    }
}

// ============================================================================
// Solver (State Machine)
// ============================================================================

/// Result of reporting a key to the solver.
#[derive(Debug)]
pub enum KeyResult<'a> {
    /// All candidates have the same type for this key.
    /// The deserializer can parse the value directly.
    Unambiguous {
        /// The shape all candidates expect for this field
        shape: &'static Shape,
    },

    /// Candidates have different types for this key - need disambiguation.
    /// Deserializer should parse the value, determine which fields it can
    /// satisfy, and call `satisfy()` with the viable fields.
    ///
    /// **Important**: When multiple fields can be satisfied by the value,
    /// pick the one with the lowest score (most specific). Scores are assigned
    /// by specificity, e.g., `u8` has a lower score than `u16`.
    Ambiguous {
        /// The unique fields across remaining candidates (deduplicated by shape),
        /// paired with a specificity score. Lower score = more specific type.
        /// Deserializer should check which of these the value can satisfy,
        /// then pick the one with the lowest score.
        fields: Vec<(&'a FieldInfo, u64)>,
    },

    /// This key disambiguated to exactly one configuration.
    Solved(ResolutionHandle<'a>),

    /// This key doesn't exist in any remaining candidate.
    Unknown,
}

/// Result of reporting which fields the value can satisfy.
#[derive(Debug)]
pub enum SatisfyResult<'a> {
    /// Continue - still multiple candidates, keep feeding keys.
    Continue,

    /// Solved to exactly one configuration.
    Solved(ResolutionHandle<'a>),

    /// No configuration can accept the value (no fields were satisfied).
    NoMatch,
}

/// State machine solver for lazy value-based disambiguation.
///
/// This solver only requests value inspection when candidates disagree on type.
/// For keys where all candidates expect the same type, the deserializer can
/// skip detailed value analysis.
///
/// # Example
///
/// ```rust
/// use facet::Facet;
/// use facet_solver::{Schema, Solver, KeyResult, SatisfyResult};
///
/// #[derive(Facet)]
/// #[repr(u8)]
/// enum NumericValue {
///     Small(u8),
///     Large(u16),
/// }
///
/// #[derive(Facet)]
/// struct Container {
///     #[facet(flatten)]
///     value: NumericValue,
/// }
///
/// let schema = Schema::build(Container::SHAPE).unwrap();
/// let mut solver = Solver::new(&schema);
///
/// // The field "0" has different types (u8 vs u16) - solver needs disambiguation
/// match solver.see_key("0") {
///     KeyResult::Ambiguous { fields } => {
///         // Deserializer sees value "1000", checks which fields can accept it
///         // u8 can't hold 1000, u16 can - so only report the u16 field
///         // Fields come with specificity scores - lower = more specific
///         let satisfied: Vec<_> = fields.iter()
///             .filter(|(f, _score)| {
///                 // deserializer's logic: can this value parse as this field's type?
///                 f.value_shape.type_identifier == "u16"
///             })
///             .map(|(f, _)| *f)
///             .collect();
///
///         match solver.satisfy(&satisfied) {
///             SatisfyResult::Solved(config) => {
///                 assert!(config.resolution().describe().contains("Large"));
///             }
///             _ => panic!("expected solved"),
///         }
///     }
///     _ => panic!("expected Ambiguous"),
/// }
/// ```
#[derive(Debug)]
pub struct Solver<'a> {
    /// Reference to the schema for configuration lookup
    schema: &'a Schema,
    /// Bitmask of remaining candidate configuration indices
    candidates: ResolutionSet,
    /// Set of seen keys for required field checking.
    /// Uses Cow to allow both borrowed keys (zero-copy) and owned keys (when needed).
    seen_keys: BTreeSet<Cow<'a, str>>,
}

impl<'a> Solver<'a> {
    /// Create a new solver from a schema.
    pub fn new(schema: &'a Schema) -> Self {
        Self {
            schema,
            candidates: ResolutionSet::full(schema.resolutions.len()),
            seen_keys: BTreeSet::new(),
        }
    }

    /// Report a key. Returns what to do next.
    ///
    /// - `Unambiguous`: All candidates agree on the type - parse directly
    /// - `Ambiguous`: Types differ - check which fields the value can satisfy
    /// - `Solved`: Disambiguated to one config
    /// - `Unknown`: Key not found in any candidate
    ///
    /// Accepts both borrowed (`&str`) and owned (`String`) keys via `Cow`.
    pub fn see_key(&mut self, key: impl Into<Cow<'a, str>>) -> KeyResult<'a> {
        let key = key.into();
        self.seen_keys.insert(key.clone());

        // Key-based filtering
        let resolutions_with_key = match self.schema.field_to_resolutions.get(key.as_ref()) {
            Some(set) => set,
            None => return KeyResult::Unknown,
        };

        self.candidates.intersect_with(resolutions_with_key);

        if self.candidates.is_empty() {
            return KeyResult::Unknown;
        }

        // Check if we've disambiguated to exactly one
        if self.candidates.len() == 1 {
            let idx = self.candidates.first().unwrap();
            return KeyResult::Solved(self.handle(idx));
        }

        // Collect unique fields (by shape pointer) across remaining candidates
        let mut unique_fields: Vec<&'a FieldInfo> = Vec::new();
        for idx in self.candidates.iter() {
            let config = &self.schema.resolutions[idx];
            if let Some(info) = config.field(key.as_ref()) {
                // Deduplicate by shape pointer
                if !unique_fields
                    .iter()
                    .any(|f| core::ptr::eq(f.value_shape, info.value_shape))
                {
                    unique_fields.push(info);
                }
            }
        }

        if unique_fields.len() == 1 {
            // All candidates have the same type - unambiguous
            KeyResult::Unambiguous {
                shape: unique_fields[0].value_shape,
            }
        } else {
            // Different types - need disambiguation
            // Attach specificity scores so caller can pick most specific when multiple match
            let fields_with_scores: Vec<_> = unique_fields
                .into_iter()
                .map(|f| (f, specificity_score(f.value_shape)))
                .collect();
            KeyResult::Ambiguous {
                fields: fields_with_scores,
            }
        }
    }

    /// Report which fields the value can satisfy after `Ambiguous` result.
    ///
    /// The deserializer should pass the subset of fields (from the `Ambiguous` result)
    /// that the actual value can be parsed into.
    pub fn satisfy(&mut self, satisfied_fields: &[&FieldInfo]) -> SatisfyResult<'a> {
        let satisfied_shapes: Vec<_> = satisfied_fields.iter().map(|f| f.value_shape).collect();
        self.satisfy_shapes(&satisfied_shapes)
    }

    /// Report which shapes the value can satisfy after `Ambiguous` result from `probe_key`.
    ///
    /// This is the shape-based version of `satisfy`, used when disambiguating
    /// by nested field types. The deserializer should pass the shapes that
    /// the actual value can be parsed into.
    ///
    /// # Example
    ///
    /// ```rust
    /// use facet::Facet;
    /// use facet_solver::{Schema, Solver, KeyResult, SatisfyResult};
    ///
    /// #[derive(Facet)]
    /// struct SmallPayload { value: u8 }
    ///
    /// #[derive(Facet)]
    /// struct LargePayload { value: u16 }
    ///
    /// #[derive(Facet)]
    /// #[repr(u8)]
    /// enum PayloadKind {
    ///     Small { payload: SmallPayload },
    ///     Large { payload: LargePayload },
    /// }
    ///
    /// #[derive(Facet)]
    /// struct Container {
    ///     #[facet(flatten)]
    ///     inner: PayloadKind,
    /// }
    ///
    /// let schema = Schema::build(Container::SHAPE).unwrap();
    /// let mut solver = Solver::new(&schema);
    ///
    /// // Report nested key
    /// solver.probe_key(&[], "payload");
    ///
    /// // At payload.value, value is 1000 - doesn't fit u8
    /// // Get shapes at this path
    /// let shapes = solver.get_shapes_at_path(&["payload", "value"]);
    /// // Filter to shapes that can hold 1000
    /// let works: Vec<_> = shapes.iter()
    ///     .filter(|s| s.type_identifier == "u16")
    ///     .copied()
    ///     .collect();
    /// solver.satisfy_shapes(&works);
    /// ```
    pub fn satisfy_shapes(&mut self, satisfied_shapes: &[&'static Shape]) -> SatisfyResult<'a> {
        if satisfied_shapes.is_empty() {
            self.candidates = ResolutionSet::empty(self.schema.resolutions.len());
            return SatisfyResult::NoMatch;
        }

        let mut new_candidates = ResolutionSet::empty(self.schema.resolutions.len());
        for idx in self.candidates.iter() {
            let config = &self.schema.resolutions[idx];
            // Check if any of this config's fields match the satisfied shapes
            for field in config.fields().values() {
                if satisfied_shapes
                    .iter()
                    .any(|s| core::ptr::eq(*s, field.value_shape))
                {
                    new_candidates.insert(idx);
                    break;
                }
            }
        }
        self.candidates = new_candidates;

        match self.candidates.len() {
            0 => SatisfyResult::NoMatch,
            1 => {
                let idx = self.candidates.first().unwrap();
                SatisfyResult::Solved(self.handle(idx))
            }
            _ => SatisfyResult::Continue,
        }
    }

    /// Get the shapes at a nested path across all remaining candidates.
    ///
    /// This is useful when you have an `Ambiguous` result from `probe_key`
    /// and need to know what types are possible at that path.
    pub fn get_shapes_at_path(&self, path: &[&str]) -> Vec<&'static Shape> {
        let mut shapes: Vec<&'static Shape> = Vec::new();
        for idx in self.candidates.iter() {
            let config = &self.schema.resolutions[idx];
            if let Some(shape) = self.get_shape_at_path(config, path)
                && !shapes.iter().any(|s| core::ptr::eq(*s, shape))
            {
                shapes.push(shape);
            }
        }
        shapes
    }

    /// Report which shapes at a nested path the value can satisfy.
    ///
    /// This is the path-aware version of `satisfy_shapes`, used when disambiguating
    /// by nested field types after `probe_key`.
    ///
    /// - `path`: The full path to the field (e.g., `["payload", "value"]`)
    /// - `satisfied_shapes`: The shapes that the value can be parsed into
    pub fn satisfy_at_path(
        &mut self,
        path: &[&str],
        satisfied_shapes: &[&'static Shape],
    ) -> SatisfyResult<'a> {
        if satisfied_shapes.is_empty() {
            self.candidates = ResolutionSet::empty(self.schema.resolutions.len());
            return SatisfyResult::NoMatch;
        }

        // Keep only candidates where the shape at this path is in the satisfied set
        let mut new_candidates = ResolutionSet::empty(self.schema.resolutions.len());
        for idx in self.candidates.iter() {
            let config = &self.schema.resolutions[idx];
            if let Some(shape) = self.get_shape_at_path(config, path)
                && satisfied_shapes.iter().any(|s| core::ptr::eq(*s, shape))
            {
                new_candidates.insert(idx);
            }
        }
        self.candidates = new_candidates;

        match self.candidates.len() {
            0 => SatisfyResult::NoMatch,
            1 => {
                let idx = self.candidates.first().unwrap();
                SatisfyResult::Solved(self.handle(idx))
            }
            _ => SatisfyResult::Continue,
        }
    }

    /// Get the current candidate resolutions.
    pub fn candidates(&self) -> Vec<ResolutionHandle<'a>> {
        self.candidates.iter().map(|idx| self.handle(idx)).collect()
    }

    /// Get the seen keys.
    pub fn seen_keys(&self) -> &BTreeSet<Cow<'a, str>> {
        &self.seen_keys
    }

    #[inline]
    fn handle(&self, idx: usize) -> ResolutionHandle<'a> {
        ResolutionHandle::from_schema(self.schema, idx)
    }

    /// Hint that a specific enum variant should be selected.
    ///
    /// This filters the candidates to only those resolutions where at least one
    /// variant selection has the given variant name. This is useful for explicit
    /// type disambiguation via annotations (e.g., KDL type annotations like `(Http)node`).
    ///
    /// Returns `true` if at least one candidate remains after filtering, `false` if
    /// no candidates match the variant name (in which case candidates are unchanged).
    ///
    /// # Example
    ///
    /// ```rust
    /// use facet::Facet;
    /// use facet_solver::{Schema, Solver};
    ///
    /// #[derive(Facet)]
    /// struct HttpSource { url: String }
    ///
    /// #[derive(Facet)]
    /// struct GitSource { url: String, branch: String }
    ///
    /// #[derive(Facet)]
    /// #[repr(u8)]
    /// enum SourceKind {
    ///     Http(HttpSource),
    ///     Git(GitSource),
    /// }
    ///
    /// #[derive(Facet)]
    /// struct Source {
    ///     #[facet(flatten)]
    ///     kind: SourceKind,
    /// }
    ///
    /// let schema = Schema::build(Source::SHAPE).unwrap();
    /// let mut solver = Solver::new(&schema);
    ///
    /// // Without hint, both variants are candidates
    /// assert_eq!(solver.candidates().len(), 2);
    ///
    /// // Hint at Http variant
    /// assert!(solver.hint_variant("Http"));
    /// assert_eq!(solver.candidates().len(), 1);
    /// ```
    pub fn hint_variant(&mut self, variant_name: &str) -> bool {
        // Build a set of configs that have this variant name
        let mut matching = ResolutionSet::empty(self.schema.resolutions.len());

        for idx in self.candidates.iter() {
            let config = &self.schema.resolutions[idx];
            // Check if any variant selection matches the given name
            if config
                .variant_selections()
                .iter()
                .any(|vs| vs.variant_name == variant_name)
            {
                matching.insert(idx);
            }
        }

        if matching.is_empty() {
            // No matches - keep candidates unchanged
            false
        } else {
            self.candidates = matching;
            true
        }
    }

    /// Mark a key as seen without filtering candidates.
    ///
    /// This is useful when the key is known to be present through means other than
    /// parsing (e.g., type annotations). Call this after `hint_variant` to mark
    /// the variant name as seen so that `finish()` doesn't report it as missing.
    pub fn mark_seen(&mut self, key: impl Into<Cow<'a, str>>) {
        self.seen_keys.insert(key.into());
    }

    /// Report a key at a nested path. Returns what to do next.
    ///
    /// This is the depth-aware version of `see_key`. Use this when probing
    /// nested structures where disambiguation might require looking inside objects.
    ///
    /// - `path`: The ancestor keys (e.g., `["payload"]` when inside a payload object)
    /// - `key`: The key found at this level (e.g., `"value"`)
    ///
    /// # Example
    ///
    /// ```rust
    /// use facet::Facet;
    /// use facet_solver::{Schema, Solver, KeyResult};
    ///
    /// #[derive(Facet)]
    /// struct SmallPayload { value: u8 }
    ///
    /// #[derive(Facet)]
    /// struct LargePayload { value: u16 }
    ///
    /// #[derive(Facet)]
    /// #[repr(u8)]
    /// enum PayloadKind {
    ///     Small { payload: SmallPayload },
    ///     Large { payload: LargePayload },
    /// }
    ///
    /// #[derive(Facet)]
    /// struct Container {
    ///     #[facet(flatten)]
    ///     inner: PayloadKind,
    /// }
    ///
    /// let schema = Schema::build(Container::SHAPE).unwrap();
    /// let mut solver = Solver::new(&schema);
    ///
    /// // "payload" exists in both - keep going
    /// solver.probe_key(&[], "payload");
    ///
    /// // "value" inside payload - both have it but different types!
    /// match solver.probe_key(&["payload"], "value") {
    ///     KeyResult::Ambiguous { fields } => {
    ///         // fields is Vec<(&FieldInfo, u64)> - field + specificity score
    ///         // Deserializer checks: 1000 fits u16 but not u8
    ///         // When multiple match, pick the one with lowest score (most specific)
    ///     }
    ///     _ => {}
    /// }
    /// ```
    pub fn probe_key(&mut self, path: &[&str], key: &str) -> KeyResult<'a> {
        // Build full path
        let mut full_path: Vec<&str> = path.to_vec();
        full_path.push(key);

        // Filter candidates to only those that have this key path
        let mut new_candidates = ResolutionSet::empty(self.schema.resolutions.len());
        for idx in self.candidates.iter() {
            let config = &self.schema.resolutions[idx];
            if config.has_key_path(&full_path) {
                new_candidates.insert(idx);
            }
        }
        self.candidates = new_candidates;

        if self.candidates.is_empty() {
            return KeyResult::Unknown;
        }

        // Check if we've disambiguated to exactly one
        if self.candidates.len() == 1 {
            let idx = self.candidates.first().unwrap();
            return KeyResult::Solved(self.handle(idx));
        }

        // Get the shape at this path for each remaining candidate
        // We need to traverse the type tree to find the actual field type
        let mut unique_shapes: Vec<(&'static Shape, usize)> = Vec::new(); // (shape, resolution_idx)

        for idx in self.candidates.iter() {
            let config = &self.schema.resolutions[idx];
            if let Some(shape) = self.get_shape_at_path(config, &full_path) {
                // Deduplicate by shape pointer
                if !unique_shapes.iter().any(|(s, _)| core::ptr::eq(*s, shape)) {
                    unique_shapes.push((shape, idx));
                }
            }
        }

        match unique_shapes.len() {
            0 => KeyResult::Unknown,
            1 => {
                // All candidates have the same type at this path - unambiguous
                KeyResult::Unambiguous {
                    shape: unique_shapes[0].0,
                }
            }
            _ => {
                // Different types at this path - need disambiguation
                // Build FieldInfo with scores for each unique shape
                let fields: Vec<(&'a FieldInfo, u64)> = unique_shapes
                    .iter()
                    .filter_map(|(shape, idx)| {
                        let config = &self.schema.resolutions[*idx];
                        // For nested paths, we need the parent field
                        // e.g., for ["payload", "value"], get the "payload" field
                        let field = if path.is_empty() {
                            config.field(key)
                        } else {
                            // Return the top-level field that contains this path
                            config.field(path[0])
                        }?;
                        Some((field, specificity_score(shape)))
                    })
                    .collect();

                KeyResult::Ambiguous { fields }
            }
        }
    }

    /// Get the shape at a nested path within a configuration.
    fn get_shape_at_path(&self, config: &'a Resolution, path: &[&str]) -> Option<&'static Shape> {
        if path.is_empty() {
            return None;
        }

        // Start with the top-level field
        let top_field = config.field(path[0])?;
        let mut current_shape = top_field.value_shape;

        // Navigate through nested structs
        for &key in &path[1..] {
            current_shape = self.get_field_shape(current_shape, key)?;
        }

        Some(current_shape)
    }

    /// Get the shape of a field within a struct shape.
    fn get_field_shape(&self, shape: &'static Shape, field_name: &str) -> Option<&'static Shape> {
        use facet_core::{StructType, Type, UserType};

        match shape.ty {
            Type::User(UserType::Struct(StructType { fields, .. })) => {
                for field in fields {
                    if field.name == field_name {
                        return Some(field.shape());
                    }
                }
                None
            }
            _ => None,
        }
    }

    /// Finish solving. Call this after all keys have been processed.
    ///
    /// This method is necessary because key-based filtering alone cannot disambiguate
    /// when one variant's required fields are a subset of another's.
    ///
    /// # Why not just use `see_key()` results?
    ///
    /// `see_key()` returns `Solved` when a key *excludes* candidates down to one.
    /// But when the input is a valid subset of multiple variants, no key excludes
    /// anything — you need `finish()` to check which candidates have all their
    /// required fields satisfied.
    ///
    /// # Example
    ///
    /// ```rust,ignore
    /// enum Source {
    ///     Http { url: String },                  // required: url
    ///     Git { url: String, branch: String },   // required: url, branch
    /// }
    /// ```
    ///
    /// | Input                  | `see_key` behavior                        | Resolution            |
    /// |------------------------|-------------------------------------------|-----------------------|
    /// | `{ "url", "branch" }`  | `branch` excludes `Http` → candidates = 1 | Early `Solved(Git)`   |
    /// | `{ "url" }`            | both have `url` → candidates = 2          | `finish()` → `Http`   |
    ///
    /// In the second case, no key ever excludes a candidate. Only `finish()` can
    /// determine that `Git` is missing its required `branch` field, leaving `Http`
    /// as the sole viable configuration.
    #[allow(clippy::result_large_err)] // SolverError intentionally contains detailed diagnostic info
    pub fn finish(self) -> Result<ResolutionHandle<'a>, SolverError> {
        let Solver {
            schema,
            candidates,
            seen_keys,
        } = self;

        // Compute all known fields across all resolutions (for unknown field detection)
        let all_known_fields: BTreeSet<&'static str> = schema
            .resolutions
            .iter()
            .flat_map(|r| r.fields().keys().copied())
            .collect();

        // Find unknown fields (fields in input that don't exist in ANY resolution)
        let unknown_fields: Vec<String> = seen_keys
            .iter()
            .filter(|k| !all_known_fields.contains(k.as_ref()))
            .map(|s| s.to_string())
            .collect();

        // Compute suggestions for unknown fields
        let suggestions = compute_suggestions(&unknown_fields, &all_known_fields);

        if candidates.is_empty() {
            // Build per-candidate failure info for all resolutions
            let mut candidate_failures: Vec<CandidateFailure> = schema
                .resolutions
                .iter()
                .map(|config| build_candidate_failure(config, &seen_keys))
                .collect();

            // Sort by closeness (best match first)
            sort_candidates_by_closeness(&mut candidate_failures);

            return Err(SolverError::NoMatch {
                input_fields: seen_keys.iter().map(|s| s.to_string()).collect(),
                missing_required: Vec::new(),
                missing_required_detailed: Vec::new(),
                unknown_fields,
                closest_resolution: None,
                candidate_failures,
                suggestions,
            });
        }

        // Filter candidates to only those that have all required fields satisfied
        let viable: Vec<usize> = candidates
            .iter()
            .filter(|idx| {
                let config = &schema.resolutions[*idx];
                config
                    .required_field_names()
                    .iter()
                    .all(|f| seen_keys.iter().any(|k| k.as_ref() == *f))
            })
            .collect();

        match viable.len() {
            0 => {
                // No viable candidates - build per-candidate failure info
                let mut candidate_failures: Vec<CandidateFailure> = candidates
                    .iter()
                    .map(|idx| {
                        let config = &schema.resolutions[idx];
                        build_candidate_failure(config, &seen_keys)
                    })
                    .collect();

                // Sort by closeness (best match first)
                sort_candidates_by_closeness(&mut candidate_failures);

                // For backwards compatibility, also populate the "closest" fields
                // Now use the first (closest) candidate after sorting
                let closest_name = candidate_failures.first().map(|f| f.variant_name.clone());
                let closest_config = closest_name
                    .as_ref()
                    .and_then(|name| schema.resolutions.iter().find(|r| r.describe() == *name));

                let (missing, missing_detailed, closest_resolution) =
                    if let Some(config) = closest_config {
                        let missing: Vec<_> = config
                            .required_field_names()
                            .iter()
                            .filter(|f| !seen_keys.iter().any(|k| k.as_ref() == **f))
                            .copied()
                            .collect();
                        let missing_detailed: Vec<_> = missing
                            .iter()
                            .filter_map(|name| config.field(name))
                            .map(MissingFieldInfo::from_field_info)
                            .collect();
                        (missing, missing_detailed, Some(config.describe()))
                    } else {
                        (Vec::new(), Vec::new(), None)
                    };

                Err(SolverError::NoMatch {
                    input_fields: seen_keys.iter().map(|s| s.to_string()).collect(),
                    missing_required: missing,
                    missing_required_detailed: missing_detailed,
                    unknown_fields,
                    closest_resolution,
                    candidate_failures,
                    suggestions,
                })
            }
            1 => {
                // Exactly one viable candidate - success!
                Ok(ResolutionHandle::from_schema(schema, viable[0]))
            }
            _ => {
                // Multiple viable candidates - ambiguous!
                let configs: Vec<_> = viable.iter().map(|&idx| &schema.resolutions[idx]).collect();
                let candidates: Vec<String> = configs.iter().map(|c| c.describe()).collect();
                let disambiguating_fields = find_disambiguating_fields(&configs);

                Err(SolverError::Ambiguous {
                    candidates,
                    disambiguating_fields,
                })
            }
        }
    }
}

/// Build a CandidateFailure for a resolution given the seen keys.
fn build_candidate_failure<'a>(
    config: &Resolution,
    seen_keys: &BTreeSet<Cow<'a, str>>,
) -> CandidateFailure {
    let missing_fields: Vec<MissingFieldInfo> = config
        .required_field_names()
        .iter()
        .filter(|f| !seen_keys.iter().any(|k| k.as_ref() == **f))
        .filter_map(|f| config.field(f))
        .map(MissingFieldInfo::from_field_info)
        .collect();

    let unknown_fields: Vec<String> = seen_keys
        .iter()
        .filter(|k| !config.fields().contains_key(k.as_ref()))
        .map(|s| s.to_string())
        .collect();

    // Compute closeness score for ranking
    let suggestion_matches = compute_closeness_score(&unknown_fields, &missing_fields, config);

    CandidateFailure {
        variant_name: config.describe(),
        missing_fields,
        unknown_fields,
        suggestion_matches,
    }
}

/// Compute a closeness score for ranking candidates.
/// Higher score = more likely the user intended this variant.
///
/// The score considers:
/// - Typo matches: unknown fields that are similar to known fields (weighted by similarity)
/// - Field coverage: if we fixed typos, would we have all required fields?
/// - Missing fields: fewer missing = better
/// - Unknown fields: fewer truly unknown (no suggestion) = better
#[cfg(feature = "suggestions")]
fn compute_closeness_score(
    unknown_fields: &[String],
    missing_fields: &[MissingFieldInfo],
    config: &Resolution,
) -> usize {
    const SIMILARITY_THRESHOLD: f64 = 0.6;

    // Score components (scaled to integers for easy comparison)
    let mut typo_score: usize = 0;
    let mut fields_that_would_match: usize = 0;

    // For each unknown field, find best matching known field
    for unknown in unknown_fields {
        let mut best_similarity = 0.0f64;
        let mut best_match: Option<&str> = None;

        for known in config.fields().keys() {
            let similarity = strsim::jaro_winkler(unknown, known);
            if similarity >= SIMILARITY_THRESHOLD && similarity > best_similarity {
                best_similarity = similarity;
                best_match = Some(known);
            }
        }

        if let Some(_matched_field) = best_match {
            // Weight by similarity: 0.6 -> 60 points, 1.0 -> 100 points
            typo_score += (best_similarity * 100.0) as usize;
            fields_that_would_match += 1;
        }
    }

    // Calculate how many required fields would be satisfied if typos were fixed
    let required_count = config.required_field_names().len();
    let currently_missing = missing_fields.len();
    let would_be_missing = currently_missing.saturating_sub(fields_that_would_match);

    // Coverage score: percentage of required fields that would be present
    let coverage_score = if required_count > 0 {
        ((required_count - would_be_missing) * 100) / required_count
    } else {
        100 // No required fields = perfect coverage
    };

    // Penalty for truly unknown fields (no typo suggestion)
    let truly_unknown = unknown_fields.len().saturating_sub(fields_that_would_match);
    let unknown_penalty = truly_unknown * 10;

    // Combine scores: typo matches are most important, then coverage, then penalties
    // Each typo match can give up to 100 points, so scale coverage to match
    typo_score + coverage_score.saturating_sub(unknown_penalty)
}

/// Compute closeness score (no-op without suggestions feature).
#[cfg(not(feature = "suggestions"))]
fn compute_closeness_score(
    _unknown_fields: &[String],
    _missing_fields: &[MissingFieldInfo],
    _config: &Resolution,
) -> usize {
    0
}

/// Sort candidate failures by closeness (best match first).
fn sort_candidates_by_closeness(failures: &mut [CandidateFailure]) {
    failures.sort_by(|a, b| {
        // Higher suggestion_matches (closeness score) first
        b.suggestion_matches.cmp(&a.suggestion_matches)
    });
}

/// Compute "did you mean?" suggestions for unknown fields.
#[cfg(feature = "suggestions")]
fn compute_suggestions(
    unknown_fields: &[String],
    all_known_fields: &BTreeSet<&'static str>,
) -> Vec<FieldSuggestion> {
    const SIMILARITY_THRESHOLD: f64 = 0.6;

    let mut suggestions = Vec::new();

    for unknown in unknown_fields {
        let mut best_match: Option<(&'static str, f64)> = None;

        for known in all_known_fields {
            let similarity = strsim::jaro_winkler(unknown, known);
            if similarity >= SIMILARITY_THRESHOLD
                && best_match.is_none_or(|(_, best_sim)| similarity > best_sim)
            {
                best_match = Some((known, similarity));
            }
        }

        if let Some((suggestion, similarity)) = best_match {
            suggestions.push(FieldSuggestion {
                unknown: unknown.clone(),
                suggestion,
                similarity,
            });
        }
    }

    suggestions
}

/// Compute "did you mean?" suggestions for unknown fields (no-op without strsim).
#[cfg(not(feature = "suggestions"))]
fn compute_suggestions(
    _unknown_fields: &[String],
    _all_known_fields: &BTreeSet<&'static str>,
) -> Vec<FieldSuggestion> {
    Vec::new()
}

// ============================================================================
// Probing Solver (Depth-Aware)
// ============================================================================

/// Result of reporting a key to the probing solver.
#[derive(Debug)]
pub enum ProbeResult<'a> {
    /// Keep reporting keys - not yet disambiguated
    KeepGoing,
    /// Solved! Use this configuration
    Solved(&'a Resolution),
    /// No configuration matches the observed keys
    NoMatch,
}

/// Depth-aware probing solver for streaming deserialization.
///
/// Unlike the batch solver, this solver accepts
/// key reports at arbitrary depths. It's designed for the "peek" strategy:
///
/// 1. Deserializer scans keys (without parsing values) and reports them
/// 2. Solver filters candidates based on which configs have that key path
/// 3. Once one candidate remains, solver returns `Solved`
/// 4. Deserializer rewinds and parses into the resolved type
///
/// # Example
///
/// ```rust
/// use facet::Facet;
/// use facet_solver::{Schema, ProbingSolver, ProbeResult};
///
/// #[derive(Facet)]
/// struct TextPayload { content: String }
///
/// #[derive(Facet)]
/// struct BinaryPayload { bytes: Vec<u8> }
///
/// #[derive(Facet)]
/// #[repr(u8)]
/// enum MessageKind {
///     Text { payload: TextPayload },
///     Binary { payload: BinaryPayload },
/// }
///
/// #[derive(Facet)]
/// struct Message {
///     id: String,
///     #[facet(flatten)]
///     kind: MessageKind,
/// }
///
/// let schema = Schema::build(Message::SHAPE).unwrap();
/// let mut solver = ProbingSolver::new(&schema);
///
/// // "id" exists in both configs - keep going
/// assert!(matches!(solver.probe_key(&[], "id"), ProbeResult::KeepGoing));
///
/// // "payload" exists in both configs - keep going
/// assert!(matches!(solver.probe_key(&[], "payload"), ProbeResult::KeepGoing));
///
/// // "content" inside payload only exists in Text - solved!
/// match solver.probe_key(&["payload"], "content") {
///     ProbeResult::Solved(config) => {
///         assert!(config.has_key_path(&["payload", "content"]));
///     }
///     _ => panic!("expected Solved"),
/// }
/// ```
#[derive(Debug)]
pub struct ProbingSolver<'a> {
    /// Remaining candidate resolutions
    candidates: Vec<&'a Resolution>,
}

impl<'a> ProbingSolver<'a> {
    /// Create a new probing solver from a schema.
    pub fn new(schema: &'a Schema) -> Self {
        Self {
            candidates: schema.resolutions.iter().collect(),
        }
    }

    /// Create a new probing solver from resolutions directly.
    pub fn from_resolutions(configs: &'a [Resolution]) -> Self {
        Self {
            candidates: configs.iter().collect(),
        }
    }

    /// Report a key found at a path during probing.
    ///
    /// - `path`: The ancestor keys (e.g., `["payload"]` when inside the payload object)
    /// - `key`: The key found at this level (e.g., `"content"`)
    ///
    /// Returns what to do next.
    pub fn probe_key(&mut self, path: &[&str], key: &str) -> ProbeResult<'a> {
        // Build the full key path (runtime strings, compared against static schema)
        let mut full_path: Vec<&str> = path.to_vec();
        full_path.push(key);

        // Filter to candidates that have this key path
        self.candidates.retain(|c| c.has_key_path(&full_path));

        match self.candidates.len() {
            0 => ProbeResult::NoMatch,
            1 => ProbeResult::Solved(self.candidates[0]),
            _ => ProbeResult::KeepGoing,
        }
    }

    /// Get the current candidate resolutions.
    pub fn candidates(&self) -> &[&'a Resolution] {
        &self.candidates
    }

    /// Finish probing - returns Solved if exactly one candidate remains.
    pub fn finish(&self) -> ProbeResult<'a> {
        match self.candidates.len() {
            0 => ProbeResult::NoMatch,
            1 => ProbeResult::Solved(self.candidates[0]),
            _ => ProbeResult::KeepGoing, // Still ambiguous
        }
    }
}

// ============================================================================
// Variant Format Classification
// ============================================================================

/// Classification of an enum variant's expected serialized format.
///
/// This is used by deserializers to determine how to parse untagged enum variants
/// based on the YAML/JSON/etc. value type they encounter.
#[derive(Debug, Clone, Copy, PartialEq, Eq)]
pub enum VariantFormat {
    /// Unit variant: no fields, serializes as the variant name or nothing for untagged
    Unit,

    /// Newtype variant wrapping a scalar type (String, numbers, bool, etc.)
    /// Serializes as just the scalar value for untagged enums.
    NewtypeScalar {
        /// The shape of the inner scalar type
        inner_shape: &'static Shape,
    },

    /// Newtype variant wrapping a struct
    /// Serializes as a mapping for untagged enums.
    NewtypeStruct {
        /// The shape of the inner struct type
        inner_shape: &'static Shape,
    },

    /// Newtype variant wrapping a tuple struct/tuple
    /// Serializes as a sequence for untagged enums.
    NewtypeTuple {
        /// The shape of the inner tuple type
        inner_shape: &'static Shape,
        /// Number of elements in the inner tuple
        arity: usize,
    },

    /// Newtype variant wrapping another type (enum, sequence, etc.)
    NewtypeOther {
        /// The shape of the inner type
        inner_shape: &'static Shape,
    },

    /// Tuple variant with multiple fields
    /// Serializes as a sequence for untagged enums.
    Tuple {
        /// Number of fields in the tuple
        arity: usize,
    },

    /// Struct variant with named fields
    /// Serializes as a mapping for untagged enums.
    Struct,
}

impl VariantFormat {
    /// Classify a variant's expected serialized format.
    pub fn from_variant(variant: &'static Variant) -> Self {
        use facet_core::StructKind;

        let fields = variant.data.fields;
        let kind = variant.data.kind;

        match kind {
            StructKind::Unit => VariantFormat::Unit,
            // TupleStruct and Tuple are both used for tuple-like variants
            // depending on how they're defined. Handle them the same way.
            StructKind::TupleStruct | StructKind::Tuple => {
                if fields.len() == 1 {
                    // Newtype variant - classify by inner type
                    let inner_shape = fields[0].shape();
                    if is_scalar_shape(inner_shape) {
                        VariantFormat::NewtypeScalar { inner_shape }
                    } else if let Some(arity) = tuple_struct_arity(inner_shape) {
                        VariantFormat::NewtypeTuple { inner_shape, arity }
                    } else if is_named_struct_shape(inner_shape) {
                        VariantFormat::NewtypeStruct { inner_shape }
                    } else {
                        VariantFormat::NewtypeOther { inner_shape }
                    }
                } else {
                    // Multi-field tuple variant
                    VariantFormat::Tuple {
                        arity: fields.len(),
                    }
                }
            }
            StructKind::Struct => VariantFormat::Struct,
        }
    }

    /// Returns true if this variant expects a scalar value in untagged format.
    pub fn expects_scalar(&self) -> bool {
        matches!(self, VariantFormat::NewtypeScalar { .. })
    }

    /// Returns true if this variant expects a sequence in untagged format.
    pub fn expects_sequence(&self) -> bool {
        matches!(
            self,
            VariantFormat::Tuple { .. } | VariantFormat::NewtypeTuple { .. }
        )
    }

    /// Returns true if this variant expects a mapping in untagged format.
    pub fn expects_mapping(&self) -> bool {
        matches!(
            self,
            VariantFormat::Struct | VariantFormat::NewtypeStruct { .. }
        )
    }

    /// Returns true if this is a unit variant (no data).
    pub fn is_unit(&self) -> bool {
        matches!(self, VariantFormat::Unit)
    }
}

/// Check if a shape represents a scalar type.
fn is_scalar_shape(shape: &'static Shape) -> bool {
    shape.scalar_type().is_some()
}

/// Returns the arity of a tuple struct/tuple shape, if applicable.
fn tuple_struct_arity(shape: &'static Shape) -> Option<usize> {
    use facet_core::{StructKind, Type, UserType};

    match shape.ty {
        Type::User(UserType::Struct(struct_type)) => match struct_type.kind {
            StructKind::Tuple | StructKind::TupleStruct => Some(struct_type.fields.len()),
            _ => None,
        },
        _ => None,
    }
}

/// Returns true if the shape is a named struct (non-tuple).
fn is_named_struct_shape(shape: &'static Shape) -> bool {
    use facet_core::{StructKind, Type, UserType};

    matches!(
        shape.ty,
        Type::User(UserType::Struct(struct_type)) if matches!(struct_type.kind, StructKind::Struct)
    )
}

/// Information about variants grouped by their expected format.
///
/// Used by deserializers to efficiently dispatch untagged enum parsing
/// based on the type of value encountered.
#[derive(Debug, Default)]
pub struct VariantsByFormat {
    /// Variants that expect a scalar value (newtype wrapping String, i32, etc.)
    pub scalar_variants: Vec<(&'static Variant, &'static Shape)>,

    /// Variants that expect a sequence (tuple variants)
    /// Grouped by arity for efficient matching.
    pub tuple_variants: Vec<(&'static Variant, usize)>,

    /// Variants that expect a mapping (struct variants, newtype wrapping struct)
    pub struct_variants: Vec<&'static Variant>,

    /// Unit variants (no data)
    pub unit_variants: Vec<&'static Variant>,

    /// Other variants that don't fit the above categories
    pub other_variants: Vec<&'static Variant>,
}

impl VariantsByFormat {
    /// Build variant classification for an enum shape.
    ///
    /// Returns None if the shape is not an enum.
    pub fn from_shape(shape: &'static Shape) -> Option<Self> {
        use facet_core::{Type, UserType};

        let enum_type = match shape.ty {
            Type::User(UserType::Enum(e)) => e,
            _ => return None,
        };

        let mut result = Self::default();

        for variant in enum_type.variants {
            match VariantFormat::from_variant(variant) {
                VariantFormat::Unit => {
                    result.unit_variants.push(variant);
                }
                VariantFormat::NewtypeScalar { inner_shape } => {
                    result.scalar_variants.push((variant, inner_shape));
                }
                VariantFormat::NewtypeStruct { .. } => {
                    result.struct_variants.push(variant);
                }
                VariantFormat::NewtypeTuple { arity, .. } => {
                    result.tuple_variants.push((variant, arity));
                }
                VariantFormat::NewtypeOther { .. } => {
                    result.other_variants.push(variant);
                }
                VariantFormat::Tuple { arity } => {
                    result.tuple_variants.push((variant, arity));
                }
                VariantFormat::Struct => {
                    result.struct_variants.push(variant);
                }
            }
        }

        Some(result)
    }

    /// Get tuple variants with a specific arity.
    pub fn tuple_variants_with_arity(&self, arity: usize) -> Vec<&'static Variant> {
        self.tuple_variants
            .iter()
            .filter(|(_, a)| *a == arity)
            .map(|(v, _)| *v)
            .collect()
    }

    /// Check if there are any scalar-expecting variants.
    pub fn has_scalar_variants(&self) -> bool {
        !self.scalar_variants.is_empty()
    }

    /// Check if there are any tuple-expecting variants.
    pub fn has_tuple_variants(&self) -> bool {
        !self.tuple_variants.is_empty()
    }

    /// Check if there are any struct-expecting variants.
    pub fn has_struct_variants(&self) -> bool {
        !self.struct_variants.is_empty()
    }
}

// ============================================================================
// Schema Builder
// ============================================================================

/// How enum variants are represented in the serialized format.
#[derive(Debug, Clone, PartialEq, Eq, Default)]
pub enum EnumRepr {
    /// Variant fields are flattened to the same level as other fields.
    /// Also used for `#[facet(untagged)]` enums where there's no tag at all.
    /// Used by formats like KDL, TOML where all fields appear at one level.
    /// Example: `{"name": "...", "host": "...", "port": 8080}`
    #[default]
    Flattened,

    /// Variant name is a key, variant content is nested under it.
    /// This is the default serde representation for enums.
    /// Example: `{"name": "...", "Tcp": {"host": "...", "port": 8080}}`
    ExternallyTagged,

    /// Tag field is inside the content, alongside variant fields.
    /// Used with `#[facet(tag = "type")]`.
    /// Example: `{"type": "Tcp", "host": "...", "port": 8080}`
    InternallyTagged {
        /// The name of the tag field (e.g., "type")
        tag: &'static str,
    },

    /// Tag and content are adjacent fields at the same level.
    /// Used with `#[facet(tag = "t", content = "c")]`.
    /// Example: `{"t": "Tcp", "c": {"host": "...", "port": 8080}}`
    AdjacentlyTagged {
        /// The name of the tag field (e.g., "t")
        tag: &'static str,
        /// The name of the content field (e.g., "c")
        content: &'static str,
    },
}

impl EnumRepr {
    /// Detect the enum representation from a Shape's attributes.
    ///
    /// Returns:
    /// - `Flattened` if `#[facet(untagged)]`
    /// - `InternallyTagged` if `#[facet(tag = "...")]` without content
    /// - `AdjacentlyTagged` if both `#[facet(tag = "...", content = "...")]`
    /// - `ExternallyTagged` if no attributes (the default enum representation)
    pub fn from_shape(shape: &'static Shape) -> Self {
        let tag = shape.get_tag_attr();
        let content = shape.get_content_attr();
        let untagged = shape.is_untagged();

        match (tag, content, untagged) {
            // Untagged explicitly requested
            (_, _, true) => EnumRepr::Flattened,
            // Both tag and content specified → adjacently tagged
            (Some(t), Some(c), false) => EnumRepr::AdjacentlyTagged { tag: t, content: c },
            // Only tag specified → internally tagged
            (Some(t), None, false) => EnumRepr::InternallyTagged { tag: t },
            // No attributes → default to externally tagged (variant name as key)
            (None, None, false) => EnumRepr::ExternallyTagged,
            // Content without tag is invalid, treat as externally tagged
            (None, Some(_), false) => EnumRepr::ExternallyTagged,
        }
    }
}

impl Schema {
    /// Build a schema for the given shape with flattened enum representation.
    ///
    /// Returns an error if the type definition contains conflicts, such as
    /// duplicate field names from parent and flattened structs.
    ///
    /// Note: This defaults to `Flattened` representation. For auto-detection
    /// based on `#[facet(tag = "...")]` attributes, use [`Schema::build_auto`].
    pub fn build(shape: &'static Shape) -> Result<Self, SchemaError> {
        Self::build_with_repr(shape, EnumRepr::Flattened)
    }

    /// Build a schema with auto-detected enum representation based on each enum's attributes.
    ///
    /// This inspects each flattened enum's shape attributes to determine its representation:
    /// - `#[facet(untagged)]` → Flattened
    /// - `#[facet(tag = "type")]` → InternallyTagged
    /// - `#[facet(tag = "t", content = "c")]` → AdjacentlyTagged
    /// - No attributes → Flattened (for flatten solver behavior)
    ///
    /// For externally-tagged enums (variant name as key), use [`Schema::build_externally_tagged`].
    pub fn build_auto(shape: &'static Shape) -> Result<Self, SchemaError> {
        let builder = SchemaBuilder::new(shape, EnumRepr::Flattened).with_auto_detect();
        builder.into_schema()
    }

    /// Build a schema for externally-tagged enum representation (e.g., JSON).
    ///
    /// In this representation, the variant name appears as a key and the
    /// variant's content is nested under it. The solver will only expect
    /// to see the variant name as a top-level key, not the variant's fields.
    pub fn build_externally_tagged(shape: &'static Shape) -> Result<Self, SchemaError> {
        Self::build_with_repr(shape, EnumRepr::ExternallyTagged)
    }

    /// Build a schema with the specified enum representation.
    pub fn build_with_repr(shape: &'static Shape, repr: EnumRepr) -> Result<Self, SchemaError> {
        let builder = SchemaBuilder::new(shape, repr);
        builder.into_schema()
    }

    /// Get the resolutions for this schema.
    pub fn resolutions(&self) -> &[Resolution] {
        &self.resolutions
    }
}

struct SchemaBuilder {
    shape: &'static Shape,
    enum_repr: EnumRepr,
    /// If true, detect enum representation from each enum's shape attributes.
    /// If false, use `enum_repr` for all enums.
    auto_detect_enum_repr: bool,
}

impl SchemaBuilder {
    fn new(shape: &'static Shape, enum_repr: EnumRepr) -> Self {
        Self {
            shape,
            enum_repr,
            auto_detect_enum_repr: false,
        }
    }

    fn with_auto_detect(mut self) -> Self {
        self.auto_detect_enum_repr = true;
        self
    }

    fn analyze(&self) -> Result<Vec<Resolution>, SchemaError> {
        self.analyze_shape(self.shape, FieldPath::empty(), Vec::new())
    }

    /// Analyze a shape and return all possible resolutions.
    /// Returns a Vec because enums create multiple resolutions.
    ///
    /// - `current_path`: The internal field path (for FieldInfo)
    /// - `key_prefix`: The serialized key path prefix (for known_paths)
    fn analyze_shape(
        &self,
        shape: &'static Shape,
        current_path: FieldPath,
        key_prefix: KeyPath,
    ) -> Result<Vec<Resolution>, SchemaError> {
        match shape.ty {
            Type::User(UserType::Struct(struct_type)) => {
                self.analyze_struct(struct_type, current_path, key_prefix)
            }
            Type::User(UserType::Enum(enum_type)) => {
                // Enum at root level: create one configuration per variant
                self.analyze_enum(shape, enum_type, current_path, key_prefix)
            }
            _ => {
                // For non-struct types at root level, return single empty config
                Ok(vec![Resolution::new()])
            }
        }
    }

    /// Analyze an enum and return one configuration per variant.
    ///
    /// - `current_path`: The internal field path (for FieldInfo)
    /// - `key_prefix`: The serialized key path prefix (for known_paths)
    fn analyze_enum(
        &self,
        shape: &'static Shape,
        enum_type: facet_core::EnumType,
        current_path: FieldPath,
        key_prefix: KeyPath,
    ) -> Result<Vec<Resolution>, SchemaError> {
        let enum_name = shape.type_identifier;
        let mut result = Vec::new();

        for variant in enum_type.variants {
            let mut config = Resolution::new();

            // Record this variant selection
            config.add_variant_selection(current_path.clone(), enum_name, variant.name);

            let variant_path = current_path.push_variant("", variant.name);

            // Get resolutions from the variant's content
            let variant_configs =
                self.analyze_variant_content(variant, &variant_path, &key_prefix)?;

            // Merge each variant config into the base
            for variant_config in variant_configs {
                let mut final_config = config.clone();
                final_config.merge(&variant_config)?;
                result.push(final_config);
            }
        }

        Ok(result)
    }

    /// Analyze a struct and return all possible resolutions.
    ///
    /// - `current_path`: The internal field path (for FieldInfo)
    /// - `key_prefix`: The serialized key path prefix (for known_paths)
    fn analyze_struct(
        &self,
        struct_type: StructType,
        current_path: FieldPath,
        key_prefix: KeyPath,
    ) -> Result<Vec<Resolution>, SchemaError> {
        // Start with one empty configuration
        let mut configs = vec![Resolution::new()];

        // Process each field, potentially multiplying resolutions
        for field in struct_type.fields {
            configs =
                self.analyze_field_into_configs(field, &current_path, &key_prefix, configs)?;
        }

        Ok(configs)
    }

    /// Process a field and return updated resolutions.
    /// If the field is a flattened enum, this may multiply the number of configs.
    ///
    /// - `parent_path`: The internal field path to the parent (for FieldInfo)
    /// - `key_prefix`: The serialized key path prefix (for known_paths)
    fn analyze_field_into_configs(
        &self,
        field: &'static Field,
        parent_path: &FieldPath,
        key_prefix: &KeyPath,
        mut configs: Vec<Resolution>,
    ) -> Result<Vec<Resolution>, SchemaError> {
        let is_flatten = field.is_flattened();

        if is_flatten {
            // Flattened: inner keys bubble up to current level (same key_prefix)
            self.analyze_flattened_field_into_configs(field, parent_path, key_prefix, configs)
        } else {
            // Regular field: add to ALL current configs
            let field_path = parent_path.push_field(field.name);
            let required = !field.has_default() && !is_option_type(field.shape());

            // Build the key path for this field
            let mut field_key_path = key_prefix.clone();
            field_key_path.push(field.name);

            let field_info = FieldInfo {
                serialized_name: field.name,
                path: field_path,
                required,
                value_shape: field.shape(),
                field,
            };

            for config in &mut configs {
                config.add_field(field_info.clone())?;
                // Add this field's key path
                config.add_key_path(field_key_path.clone());
            }

            // If the field's value is a struct, recurse to collect nested key paths
            // (for probing, not for flattening - these are nested in serialized format)
            // This may fork resolutions if the nested struct contains flattened enums!
            configs =
                self.collect_nested_key_paths_for_shape(field.shape(), &field_key_path, configs)?;

            Ok(configs)
        }
    }

    /// Collect nested key paths from a shape into resolutions.
    /// This handles the case where a non-flattened field contains a struct with flattened enums.
    /// Returns updated resolutions (may fork if flattened enums are encountered).
    fn collect_nested_key_paths_for_shape(
        &self,
        shape: &'static Shape,
        key_prefix: &KeyPath,
        configs: Vec<Resolution>,
    ) -> Result<Vec<Resolution>, SchemaError> {
        match shape.ty {
            Type::User(UserType::Struct(struct_type)) => {
                self.collect_nested_key_paths_for_struct(struct_type, key_prefix, configs)
            }
            _ => Ok(configs),
        }
    }

    /// Collect nested key paths from a struct, potentially forking for flattened enums.
    fn collect_nested_key_paths_for_struct(
        &self,
        struct_type: StructType,
        key_prefix: &KeyPath,
        mut configs: Vec<Resolution>,
    ) -> Result<Vec<Resolution>, SchemaError> {
        for field in struct_type.fields {
            let is_flatten = field.is_flattened();
            let mut field_key_path = key_prefix.clone();

            if is_flatten {
                // Flattened field: keys bubble up to current level, may fork configs
                configs =
                    self.collect_nested_key_paths_for_flattened(field, key_prefix, configs)?;
            } else {
                // Regular field: add key path and recurse
                field_key_path.push(field.name);

                for config in &mut configs {
                    config.add_key_path(field_key_path.clone());
                }

                // Recurse into nested structs
                configs = self.collect_nested_key_paths_for_shape(
                    field.shape(),
                    &field_key_path,
                    configs,
                )?;
            }
        }
        Ok(configs)
    }

    /// Handle flattened fields when collecting nested key paths.
    /// This may fork resolutions for flattened enums.
    fn collect_nested_key_paths_for_flattened(
        &self,
        field: &'static Field,
        key_prefix: &KeyPath,
        configs: Vec<Resolution>,
    ) -> Result<Vec<Resolution>, SchemaError> {
        let shape = field.shape();

        match shape.ty {
            Type::User(UserType::Struct(struct_type)) => {
                // Flattened struct: recurse with same key_prefix
                self.collect_nested_key_paths_for_struct(struct_type, key_prefix, configs)
            }
            Type::User(UserType::Enum(enum_type)) => {
                // Flattened enum: fork resolutions
                // We need to match each config to its corresponding variant
                let mut result = Vec::new();

                for config in configs {
                    // Find which variant this config has selected for this field
                    let selected_variant = config
                        .variant_selections()
                        .iter()
                        .find(|vs| {
                            // Match by the field name in the path
                            vs.path.segments().last() == Some(&PathSegment::Field(field.name))
                        })
                        .map(|vs| vs.variant_name);

                    if let Some(variant_name) = selected_variant {
                        // Find the variant and collect its key paths
                        if let Some(variant) =
                            enum_type.variants.iter().find(|v| v.name == variant_name)
                        {
                            let mut updated_config = config;
                            updated_config = self.collect_variant_key_paths(
                                variant,
                                key_prefix,
                                updated_config,
                            )?;
                            result.push(updated_config);
                        } else {
                            result.push(config);
                        }
                    } else {
                        result.push(config);
                    }
                }
                Ok(result)
            }
            _ => Ok(configs),
        }
    }

    /// Collect key paths from an enum variant's content.
    fn collect_variant_key_paths(
        &self,
        variant: &'static Variant,
        key_prefix: &KeyPath,
        mut config: Resolution,
    ) -> Result<Resolution, SchemaError> {
        // Check if this is a newtype variant (single unnamed field)
        if variant.data.fields.len() == 1 && variant.data.fields[0].name == "0" {
            let inner_field = &variant.data.fields[0];
            let inner_shape = inner_field.shape();

            // If the inner type is a struct, flatten its fields
            if let Type::User(UserType::Struct(inner_struct)) = inner_shape.ty {
                let configs = self.collect_nested_key_paths_for_struct(
                    inner_struct,
                    key_prefix,
                    vec![config],
                )?;
                return Ok(configs.into_iter().next().unwrap_or_else(Resolution::new));
            }
        }

        // Named fields - process each
        for variant_field in variant.data.fields {
            let is_flatten = variant_field.is_flattened();

            if is_flatten {
                let configs = self.collect_nested_key_paths_for_flattened(
                    variant_field,
                    key_prefix,
                    vec![config],
                )?;
                config = configs.into_iter().next().unwrap_or_else(Resolution::new);
            } else {
                let mut field_key_path = key_prefix.clone();
                field_key_path.push(variant_field.name);
                config.add_key_path(field_key_path.clone());

                let configs = self.collect_nested_key_paths_for_shape(
                    variant_field.shape(),
                    &field_key_path,
                    vec![config],
                )?;
                config = configs.into_iter().next().unwrap_or_else(Resolution::new);
            }
        }
        Ok(config)
    }

    /// Collect ONLY key paths from a variant's content (no fields added).
    /// Used for externally-tagged enums where variant content is nested and
    /// will be parsed separately by the deserializer.
    fn collect_variant_key_paths_only(
        &self,
        variant: &'static Variant,
        key_prefix: &KeyPath,
        config: &mut Resolution,
    ) -> Result<(), SchemaError> {
        // Check if this is a newtype variant (single unnamed field)
        if variant.data.fields.len() == 1 && variant.data.fields[0].name == "0" {
            let inner_field = &variant.data.fields[0];
            let inner_shape = inner_field.shape();

            // If the inner type is a struct, add key paths for its fields
            if let Type::User(UserType::Struct(inner_struct)) = inner_shape.ty {
                Self::collect_struct_key_paths_only(inner_struct, key_prefix, config);
                return Ok(());
            }
        }

        // Named fields - add key paths for each
        for variant_field in variant.data.fields {
            let mut field_key_path = key_prefix.clone();
            field_key_path.push(variant_field.name);
            config.add_key_path(field_key_path.clone());

            // Recurse into nested structs
            if let Type::User(UserType::Struct(inner_struct)) = variant_field.shape().ty {
                Self::collect_struct_key_paths_only(inner_struct, &field_key_path, config);
            }
        }
        Ok(())
    }

    /// Recursively collect key paths from a struct (no fields added).
    fn collect_struct_key_paths_only(
        struct_type: StructType,
        key_prefix: &KeyPath,
        config: &mut Resolution,
    ) {
        for field in struct_type.fields {
            let is_flatten = field.is_flattened();

            if is_flatten {
                // Flattened field: keys bubble up to current level
                if let Type::User(UserType::Struct(inner_struct)) = field.shape().ty {
                    Self::collect_struct_key_paths_only(inner_struct, key_prefix, config);
                }
            } else {
                // Regular field: add its key path
                let mut field_key_path = key_prefix.clone();
                field_key_path.push(field.name);
                config.add_key_path(field_key_path.clone());

                // Recurse into nested structs
                if let Type::User(UserType::Struct(inner_struct)) = field.shape().ty {
                    Self::collect_struct_key_paths_only(inner_struct, &field_key_path, config);
                }
            }
        }
    }

    /// Process a flattened field, potentially forking resolutions for enums.
    ///
    /// For flattened fields, the inner keys bubble up to the current level,
    /// so we pass the same key_prefix (not key_prefix + field.name).
    ///
    /// If the field is `Option<T>`, we unwrap to get T and mark all resulting
    /// fields as optional (since the entire flattened block can be omitted).
    fn analyze_flattened_field_into_configs(
        &self,
        field: &'static Field,
        parent_path: &FieldPath,
        key_prefix: &KeyPath,
        configs: Vec<Resolution>,
    ) -> Result<Vec<Resolution>, SchemaError> {
        let field_path = parent_path.push_field(field.name);
        let original_shape = field.shape();

        // Check if this is Option<T> - if so, unwrap and mark all fields optional
        let (shape, is_optional_flatten) = match unwrap_option_type(original_shape) {
            Some(inner) => (inner, true),
            None => (original_shape, false),
        };

        match shape.ty {
            Type::User(UserType::Struct(struct_type)) => {
                // Flatten a struct: get its resolutions and merge into each of ours
                // Key prefix stays the same - inner keys bubble up
                let mut struct_configs =
                    self.analyze_struct(struct_type, field_path, key_prefix.clone())?;

                // If the flatten field was Option<T>, mark all inner fields as optional
                if is_optional_flatten {
                    for config in &mut struct_configs {
                        config.mark_all_optional();
                    }
                }

                // Each of our configs combines with each struct config
                // (usually struct_configs has 1 element unless it contains enums)
                let mut result = Vec::new();
                for base_config in configs {
                    for struct_config in &struct_configs {
                        let mut merged = base_config.clone();
                        merged.merge(struct_config)?;
                        result.push(merged);
                    }
                }
                Ok(result)
            }
            Type::User(UserType::Enum(enum_type)) => {
                // Fork: each existing config × each variant
                let mut result = Vec::new();
                let enum_name = shape.type_identifier;

                // Determine enum representation:
                // - If auto_detect_enum_repr is enabled, detect from the enum's shape attributes
                // - Otherwise, use the global enum_repr setting
                let enum_repr = if self.auto_detect_enum_repr {
                    EnumRepr::from_shape(shape)
                } else {
                    self.enum_repr.clone()
                };

                for base_config in configs {
                    for variant in enum_type.variants {
                        let mut forked = base_config.clone();
                        forked.add_variant_selection(field_path.clone(), enum_name, variant.name);

                        let variant_path = field_path.push_variant(field.name, variant.name);

                        match &enum_repr {
                            EnumRepr::ExternallyTagged => {
                                // For externally tagged enums, the variant name is a key
                                // at the current level, and its content is nested underneath.
                                let mut variant_key_prefix = key_prefix.clone();
                                variant_key_prefix.push(variant.name);

                                // Add the variant name itself as a known key path
                                forked.add_key_path(variant_key_prefix.clone());

                                // Add the variant name as a field (the key that selects this variant)
                                let variant_field_info = FieldInfo {
                                    serialized_name: variant.name,
                                    path: variant_path.clone(),
                                    required: !is_optional_flatten,
                                    value_shape: shape, // The enum shape
                                    field,              // The original flatten field
                                };
                                forked.add_field(variant_field_info)?;

                                // For externally-tagged enums, we do NOT add the variant's
                                // inner fields to required fields. They're nested and will
                                // be parsed separately by the deserializer.
                                // Only add them to known_paths for depth-aware probing.
                                self.collect_variant_key_paths_only(
                                    variant,
                                    &variant_key_prefix,
                                    &mut forked,
                                )?;

                                result.push(forked);
                            }
                            EnumRepr::Flattened => {
                                // For flattened/untagged enums, the variant's fields appear at the
                                // same level as other fields. The variant name is NOT a key;
                                // only the variant's inner fields are keys.

                                // Get resolutions from the variant's content
                                // Key prefix stays the same - inner keys bubble up
                                let mut variant_configs = self.analyze_variant_content(
                                    variant,
                                    &variant_path,
                                    key_prefix,
                                )?;

                                // If the flatten field was Option<T>, mark all inner fields as optional
                                if is_optional_flatten {
                                    for config in &mut variant_configs {
                                        config.mark_all_optional();
                                    }
                                }

                                // Merge each variant config into the forked base
                                for variant_config in variant_configs {
                                    let mut final_config = forked.clone();
                                    final_config.merge(&variant_config)?;
                                    result.push(final_config);
                                }
                            }
                            EnumRepr::InternallyTagged { tag } => {
                                // For internally tagged enums, the tag field appears at the
                                // same level as the variant's fields.
                                // Example: {"type": "Tcp", "host": "...", "port": 8080}

                                // Add the tag field as a known key path
                                let mut tag_key_path = key_prefix.clone();
                                tag_key_path.push(tag);
                                forked.add_key_path(tag_key_path);

                                // Add the tag field info - the tag discriminates the variant
                                // We use a synthetic field for the tag
                                let tag_field_info = FieldInfo {
                                    serialized_name: tag,
                                    path: variant_path.clone(),
                                    required: !is_optional_flatten,
                                    value_shape: shape, // The enum shape
                                    field,              // The original flatten field
                                };
                                forked.add_field(tag_field_info)?;

                                // Get resolutions from the variant's content
                                // Key prefix stays the same - inner keys are at the same level
                                let mut variant_configs = self.analyze_variant_content(
                                    variant,
                                    &variant_path,
                                    key_prefix,
                                )?;

                                // If the flatten field was Option<T>, mark all inner fields as optional
                                if is_optional_flatten {
                                    for config in &mut variant_configs {
                                        config.mark_all_optional();
                                    }
                                }

                                // Merge each variant config into the forked base
                                for variant_config in variant_configs {
                                    let mut final_config = forked.clone();
                                    final_config.merge(&variant_config)?;
                                    result.push(final_config);
                                }
                            }
                            EnumRepr::AdjacentlyTagged { tag, content } => {
                                // For adjacently tagged enums, both tag and content fields
                                // appear at the same level. Content contains the variant's fields.
                                // Example: {"t": "Tcp", "c": {"host": "...", "port": 8080}}

                                // Add the tag field as a known key path
                                let mut tag_key_path = key_prefix.clone();
                                tag_key_path.push(tag);
                                forked.add_key_path(tag_key_path);

                                // Add the tag field info
                                let tag_field_info = FieldInfo {
                                    serialized_name: tag,
                                    path: variant_path.clone(),
                                    required: !is_optional_flatten,
                                    value_shape: shape, // The enum shape
                                    field,              // The original flatten field
                                };
                                forked.add_field(tag_field_info)?;

                                // Add the content field as a known key path
                                let mut content_key_prefix = key_prefix.clone();
                                content_key_prefix.push(content);
                                forked.add_key_path(content_key_prefix.clone());

                                // The variant's fields are nested under the content key
                                // Collect key paths for probing
                                self.collect_variant_key_paths_only(
                                    variant,
                                    &content_key_prefix,
                                    &mut forked,
                                )?;

                                result.push(forked);
                            }
                        }
                    }
                }
                Ok(result)
            }
            _ => {
                // Can't flatten other types - treat as regular field
                // For Option<T> flatten, also consider optionality from the wrapper
                let required =
                    !field.has_default() && !is_option_type(shape) && !is_optional_flatten;

                // For non-flattenable types, add the field with its key path
                let mut field_key_path = key_prefix.clone();
                field_key_path.push(field.name);

                let field_info = FieldInfo {
                    serialized_name: field.name,
                    path: field_path,
                    required,
                    value_shape: shape,
                    field,
                };

                let mut result = configs;
                for config in &mut result {
                    config.add_field(field_info.clone())?;
                    config.add_key_path(field_key_path.clone());
                }
                Ok(result)
            }
        }
    }

    /// Analyze a variant's content and return resolutions.
    ///
    /// - `variant_path`: The internal field path (for FieldInfo)
    /// - `key_prefix`: The serialized key path prefix (for known_paths)
    fn analyze_variant_content(
        &self,
        variant: &'static Variant,
        variant_path: &FieldPath,
        key_prefix: &KeyPath,
    ) -> Result<Vec<Resolution>, SchemaError> {
        // Check if this is a newtype variant (single unnamed field like `Foo(Bar)`)
        if variant.data.fields.len() == 1 && variant.data.fields[0].name == "0" {
            let inner_field = &variant.data.fields[0];
            let inner_shape = inner_field.shape();

            // If the inner type is a struct, treat the newtype wrapper as transparent.
            //
            // Previously we pushed a synthetic `"0"` segment onto the path. That made the
            // solver think there was an extra field between the variant and the inner
            // struct (e.g., `backend.backend::Local.0.cache`). KDL flattening does not
            // expose that tuple wrapper, so the deserializer would try to open a field
            // named `"0"` on the inner struct/enum, causing "no such field" errors when
            // navigating paths like `backend::Local.cache`.
            //
            // Keep the synthetic `"0"` segment so the solver/reflect layer walks through
            // the tuple wrapper that Rust generates for newtype variants.

            // For untagged enum variant resolution, we need to look at the "effective"
            // shape that determines the serialization format. This unwraps:
            // 1. Transparent wrappers (shape.inner) - e.g., `Curve64(GCurve<f64, f64>)`
            // 2. Proxy types (shape.proxy) - e.g., `GCurve` uses `GCurveProxy` for ser/de
            //
            // This ensures that `{"x":..., "y":...}` correctly matches `Linear(Curve64)`
            // where Curve64 is transparent around GCurve which has a proxy with x,y fields.
            let effective_shape = unwrap_to_effective_shape(inner_shape);

            if let Type::User(UserType::Struct(inner_struct)) = effective_shape.ty {
                let inner_path = variant_path.push_field("0");
                return self.analyze_struct(inner_struct, inner_path, key_prefix.clone());
            }
        }

        // Named fields or multiple fields - analyze as a pseudo-struct
        let mut configs = vec![Resolution::new()];
        for variant_field in variant.data.fields {
            configs =
                self.analyze_field_into_configs(variant_field, variant_path, key_prefix, configs)?;
        }
        Ok(configs)
    }

    fn into_schema(self) -> Result<Schema, SchemaError> {
        let resolutions = self.analyze()?;
        let num_resolutions = resolutions.len();

        // Build inverted index: field_name → bitmask of config indices
        let mut field_to_resolutions: BTreeMap<&'static str, ResolutionSet> = BTreeMap::new();
        for (idx, config) in resolutions.iter().enumerate() {
            for field_name in config.fields().keys() {
                field_to_resolutions
                    .entry(*field_name)
                    .or_insert_with(|| ResolutionSet::empty(num_resolutions))
                    .insert(idx);
            }
        }

        Ok(Schema {
            shape: self.shape,
            resolutions,
            field_to_resolutions,
        })
    }
}

/// Check if a shape represents an Option type.
fn is_option_type(shape: &'static Shape) -> bool {
    matches!(shape.def, Def::Option(_))
}

/// If shape is `Option<T>`, returns `Some(T's shape)`. Otherwise returns `None`.
fn unwrap_option_type(shape: &'static Shape) -> Option<&'static Shape> {
    match shape.def {
        Def::Option(option_def) => Some(option_def.t),
        _ => None,
    }
}

/// Unwrap transparent wrappers and proxies to get the effective shape for field matching.
///
/// When determining which untagged enum variant matches a set of fields, we need to
/// look at the "effective" shape that determines the serialization format:
///
/// 1. Transparent wrappers (shape.inner): e.g., `Curve64` wraps `GCurve<f64, f64>`
///    - The wrapper has no serialization presence; it serializes as its inner type
///
/// 2. Proxy types (shape.proxy): e.g., `GCurve` uses `GCurveProxy` for ser/de
///    - The proxy's fields are what appear in the serialized format
///
/// This function recursively unwraps these layers to find the shape whose fields
/// should be used for variant matching. For example:
/// - `Curve64` (transparent) → `GCurve<f64, f64>` (has proxy) → `GCurveProxy<f64, f64>`
fn unwrap_to_effective_shape(shape: &'static Shape) -> &'static Shape {
    // First, unwrap transparent wrappers
    let shape = unwrap_transparent(shape);

    // Then, if there's a proxy, use its shape instead
    if let Some(proxy_def) = shape.proxy {
        // Recursively unwrap in case the proxy is also transparent or has its own proxy
        unwrap_to_effective_shape(proxy_def.shape)
    } else {
        shape
    }
}

/// Recursively unwrap transparent wrappers to get to the innermost type.
fn unwrap_transparent(shape: &'static Shape) -> &'static Shape {
    if let Some(inner) = shape.inner {
        unwrap_transparent(inner)
    } else {
        shape
    }
}